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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: yusyel/bert_faq
  results: []
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->

# yusyel/bert_faq

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.7985
- Validation Loss: 0.8954
- Epoch: 13

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 896, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 1.7394     | 1.4158          | 0     |
| 1.3291     | 1.2100          | 1     |
| 1.1664     | 1.1007          | 2     |
| 1.0144     | 1.0112          | 3     |
| 0.9238     | 0.9387          | 4     |
| 0.8509     | 0.9155          | 5     |
| 0.8117     | 0.8954          | 6     |
| 0.7988     | 0.8954          | 7     |
| 0.7966     | 0.8954          | 8     |
| 0.7857     | 0.8954          | 9     |
| 0.8042     | 0.8954          | 10    |
| 0.7911     | 0.8954          | 11    |
| 0.7971     | 0.8954          | 12    |
| 0.7985     | 0.8954          | 13    |


### Framework versions

- Transformers 4.35.2
- TensorFlow 2.15.0
- Datasets 2.16.1
- Tokenizers 0.15.1